Instructions to use slow-stack/laya-nli-conflict-v10-l2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slow-stack/laya-nli-conflict-v10-l2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="slow-stack/laya-nli-conflict-v10-l2")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("slow-stack/laya-nli-conflict-v10-l2", device_map="auto") - Laya
How to use slow-stack/laya-nli-conflict-v10-l2 with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
laya-nli-conflict-v10-l2 β research archive (round 10, v9-config rerun), NOT delivered
β οΈ Research archive β NOT a delivered model. This checkpoint failed its round's acceptance gates and was never shipped. The current production head is
slow-stack/laya-nli-memory-conflict(v4). Uploaded 2026-10-02 for provenance/backup while round 11 (multi-run verdict protocol) waits for Kaggle GPU quota.
Round 10 (2026-10-01) of the laya NLI memory-conflict head program by modusensus. L2 = an independent rerun of the v9 corpus and configuration (kernel-direct, complete artifact set), completing the three-run same-config evidence together with the v9 round run and the S2 baseline (laya-nli-conflict-v10-s2).
Headline results
- main val 0.889 (β), new-10 9/10 (β), bias diagnosis 12/14 (β) β 9/12 gates
- Why this run matters: across the three byte-identical-config runs (v9 / S2 / L2) β main val 0.9050 / 0.8940 / 0.8890 (1.6pp swing), Ο(noul) 1.03β1.19, and B2 = 0.889 / 0.3877 / 0.6951 β a 50pp range crossing the 0.5 decision line. Same config, both "pass" and "fail" β single-run B2 readings have no decision power; round 11 therefore preregisters a multi-run median protocol with a 9-case isomorphic family instrument.
Artifacts
| file | value |
|---|---|
| model.safetensors | SHA256 e557d46bβ¦b98d15 (full hash in archive_sha256_manifest.txt) |
| rl_agent_config.json | Ο(noul) = 1.0284; encoder jhu-clsp/mmBERT-base; bf16 |
| metrics.json | val_accuracy 0.889, val_ece 0.0408, n_val 1000, no_rl true |
| val_probs.json | frozen-val probability dump (calibration analyses) |
Provenance
- Training: Kaggle GPU kernel
daphnelaurent/laya-nli-conflict-ce(three-version sequence), datasetdaphnelaurent/nli-conflict-pairsv15 - Round record & full gate table:
kaggle_eval/HANDOFF_NLI_V10.md
Model tree for slow-stack/laya-nli-conflict-v10-l2
Base model
convaiinnovations/laya-multilingual